The present invention relates to digital video signal processing, and more particularly to architectures and methods for digital camera front-ends.
Imaging and video capabilities have become the trend in consumer electronics. Digital cameras, digital camcorders, and video cellular phones are common, and many other new gadgets are evolving in the market. Advances in large resolution CCD/CMOS sensors coupled with the availability of low-power digital signal processors (DSPs) has led to the development of digital cameras with both high resolution image and short audio/visual clip capabilities. The high resolution (e.g., sensor with a 2560×1920 pixel array) provides quality offered by traditional film cameras.
FIG. 1 is a typical functional block diagram 100 for digital camera control and image processing, i.e. the “image pipeline” (Prior art). The automatic focus 102, automatic exposure 104 and automatic white balancing 106 are referred to as the 3 A functions. The image processing includes functions, such as, color filter array (CFA) interpolation 108, gamma correction 110, white balancing, color space conversion 112, JPEG/MPEG compression/decompression 114 (JPEG for single images and MPEG for video clips), scaling for monitor/LCD 118, edge detection 120, false color suppression 122, fault pixel correction 124, and optical black clamp 126, analog processing 128, various optic device 130, and lens distortion correction 132.
Color CCD 116 typically consists of a rectangular array of photosites (pixels) with each photosite covered by a single-color filter (the CFA): typically, red, green, or blue filters are used. In the commonly-used Bayer pattern CFA, one-half of the photosites are green, one-quarter are red, and one-quarter are blue. Each photosite in the sensor detects the incident light amplitude of an input scene for its color, and the sensor output provides a Bayer-pattern image with single-color pixels corresponding to the photosite locations. Subsequent CFA interpolation provides the two other color amplitudes for each pixel to give the full-color image of the input scene.
Typically, digital cameras provide a capture mode with full resolution image or audio/visual clip processing with compression and storage, a preview mode with lower resolution processing for immediate display, and a playback mode for displaying stored images or audio/visual clips. Sharp images are images that are compelling to human eyes. Traditional edge enhancement methods, such as, unsharp masking, are used widely in biological and medical applications. Such methods, usually, apply a highpass filter to the image and incorporate the direct or modified filtering output to the image.
These methods may enhance image sharpness with user input, but also may result in unnatural images due to noise or halo artifacts. Although these artifacts may be acceptable for some applications, many users find such artifacts unacceptable and prefer more pleasing images. In addition, digital cameras may be used in very different lighting conditions and capture images contain different contents; thus, edge enhancement for digital cameras becomes more challenging.
Therefore, there is a need for a method and a system for improved edge detection and image enhancement.